| | --- |
| | license: apache-2.0 |
| | base_model: google/vit-base-patch16-224-in21k |
| | tags: |
| | - generated_from_trainer |
| | datasets: |
| | - imagefolder |
| | metrics: |
| | - accuracy |
| | model-index: |
| | - name: image_classification |
| | results: |
| | - task: |
| | name: Image Classification |
| | type: image-classification |
| | dataset: |
| | name: imagefolder |
| | type: imagefolder |
| | config: default |
| | split: train |
| | args: default |
| | metrics: |
| | - name: Accuracy |
| | type: accuracy |
| | value: 0.56875 |
| | --- |
| | |
| | <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| | should probably proofread and complete it, then remove this comment. --> |
| |
|
| | # image_classification |
| | |
| | This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the imagefolder dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 1.2152 |
| | - Accuracy: 0.5687 |
| | |
| | ## Model description |
| | |
| | More information needed |
| | |
| | ## Intended uses & limitations |
| | |
| | More information needed |
| | |
| | ## Training and evaluation data |
| | |
| | More information needed |
| | |
| | ## Training procedure |
| | |
| | ### Training hyperparameters |
| | |
| | The following hyperparameters were used during training: |
| | - learning_rate: 5e-05 |
| | - train_batch_size: 16 |
| | - eval_batch_size: 16 |
| | - seed: 42 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: linear |
| | - num_epochs: 20 |
| | |
| | ### Training results |
| | |
| | | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| | |:-------------:|:-----:|:----:|:---------------:|:--------:| |
| | | No log | 1.0 | 40 | 1.3484 | 0.5437 | |
| | | No log | 2.0 | 80 | 1.3268 | 0.4875 | |
| | | No log | 3.0 | 120 | 1.2463 | 0.5437 | |
| | | No log | 4.0 | 160 | 1.2361 | 0.5563 | |
| | | No log | 5.0 | 200 | 1.2089 | 0.5813 | |
| | | No log | 6.0 | 240 | 1.2544 | 0.525 | |
| | | No log | 7.0 | 280 | 1.1947 | 0.5563 | |
| | | No log | 8.0 | 320 | 1.2502 | 0.5188 | |
| | | No log | 9.0 | 360 | 1.3415 | 0.4938 | |
| | | No log | 10.0 | 400 | 1.1336 | 0.6 | |
| | | No log | 11.0 | 440 | 1.2716 | 0.5437 | |
| | | No log | 12.0 | 480 | 1.4631 | 0.5 | |
| | | 0.6882 | 13.0 | 520 | 1.3970 | 0.5563 | |
| | | 0.6882 | 14.0 | 560 | 1.2654 | 0.5188 | |
| | | 0.6882 | 15.0 | 600 | 1.2498 | 0.575 | |
| | | 0.6882 | 16.0 | 640 | 1.2655 | 0.5938 | |
| | | 0.6882 | 17.0 | 680 | 1.3577 | 0.55 | |
| | | 0.6882 | 18.0 | 720 | 1.2711 | 0.5813 | |
| | | 0.6882 | 19.0 | 760 | 1.3127 | 0.5687 | |
| | | 0.6882 | 20.0 | 800 | 1.2478 | 0.575 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.33.2 |
| | - Pytorch 2.0.1+cu118 |
| | - Datasets 2.14.5 |
| | - Tokenizers 0.13.3 |
| | |
